Characterization of rattling in relation to thermal conductivity: Ordered half-Heusler semiconductors

Feng, Zhenzhen; Fu, Yuhao; Zhang, Yongsheng; Singh, David J.

doi:10.1103/physrevb.101.064301

Cited by 58 publications

(33 citation statements)

References 63 publications

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“…The observation of the LO-TO splitting in ZrNiSn confirms that HH compounds exhibit polar chemical bonds 53 . This mixed bonding can also be important for the thermal conductivity 54 . The polar coupling constant, α PO , for ZrNiSn is estimated as 0.32, indicating that the polar optical phonon scattering could play an important role in electrical transport properties.…”

Section: Resultsmentioning

confidence: 99%

Establishing the carrier scattering phase diagram for ZrNiSn-based half-Heusler thermoelectric materials

et al. 2020

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Chemical doping is one of the most important strategies for tuning electrical properties of semiconductors, particularly thermoelectric materials. Generally, the main role of chemical doping lies in optimizing the carrier concentration, but there can potentially be other important effects. Here, we show that chemical doping plays multiple roles for both electron and phonon transport properties in half-Heusler thermoelectric materials. With ZrNiSn-based half-Heusler materials as an example, we use high-quality single and polycrystalline crystals, various probes, including electrical transport measurements, inelastic neutron scattering measurement, and first-principles calculations, to investigate the underlying electron-phonon interaction. We find that chemical doping brings strong screening effects to ionized impurities, grain boundary, and polar optical phonon scattering, but has negligible influence on lattice thermal conductivity. Furthermore, it is possible to establish a carrier scattering phase diagram, which can be used to select reasonable strategies for optimization of the thermoelectric performance.

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Section: Resultsmentioning

confidence: 99%

Establishing the carrier scattering phase diagram for ZrNiSn-based half-Heusler thermoelectric materials

et al. 2020

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“…By comparison, the k l of SeTe 2 monolayers is much lower than that of Se 2 Te monolayers, as shown in Figure 7 , which is benefited from the large weight of the constituent elements [ 10 ] and weak bonding [ 51 , 52 ] (see Figure 4 ). Notably, it can be seen from Figure 7 that both the k l of Se 2 Te and SeTe 2 decrease with the biaxial tensile strain.…”

Section: Resultsmentioning

confidence: 99%

Biaxial Tensile Strain-Induced Enhancement of Thermoelectric Efficiency of α-Phase Se2Te and SeTe2 Monolayers

et al. 2021

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Thermoelectric (TE) materials can convert waste heat into electrical energy, which has attracted great interest in recent years. In this paper, the effect of biaxial-tensile strain on the electronic properties, lattice thermal conductivity, and thermoelectric performance of α-phase Se2Te and SeTe2 monolayers are calculated based on density-functional theory and the semiclassical Boltzmann theory. The calculated results show that the tensile strain reduces the bandgap because the bond length between atoms enlarges. Moreover, the tensile strain strengthens the scatting rate while it weakens the group velocity and softens the phonon model, leading to lower lattice thermal conductivity kl. Simultaneously, combined with the weakened kl, the tensile strain can also effectively modulate the electronic transport coefficients, such as the electronic conductivity, Seebeck coefficient, and electronic thermal conductivity, to greatly enhance the ZT value. In particular, the maximum n-type doping ZT under 1% and 3% strain increases up to six and five times higher than the corresponding ZT without strain for the Se2Te and SeTe2 monolayers, respectively. Our calculations indicated that the tensile strain can effectively enhance the thermoelectric efficiency of Se2Te and SeTe2 monolayers and they have great potential as TE materials.

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“…Several HH compounds have a high power factor in combination with relatively low κ , making HHs attractive for TE applications [8,13,[30][31][32][33][34][35][36]. Recently, Feng et al [37] used DFT-based calculations to show that the four HH compounds: CdPNa, BaBiK, LaRhTe, and LaPtSb have very low κ . LaPtSb and BaBiK have also have promising electronic transport properties in addition to low κ and could have a ZT competitive with the top performing TE materials [38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Lattice thermal conductivity of half-Heuslers with density functional theory and machine learning: Enhancing predictivity by active sampling with principal component analysis

Tranås¹,

Løvvik²,

Tomić³

et al. 2021

Preprint

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Low lattice thermal conductivity is essential for high thermoelectric performance of a material. Lattice thermal conductivity is often computed based on density functional theory calculations, but such calculations carry a high computational cost and machine learning is therefore increasingly being used to estimate lattice thermal conductivity at a much lower computational expense. With the ability to asses larger sets of materials, machine learning could offer an effective procedure to identify low lattice thermal conductivity compounds. However, such compounds can be quite rare and distinct from typical compounds in a given training set. This can be problematic as standard machine learning methods lack the ability to precisely interpret properties of compounds with features differing significantly from those in the training set. By computing the lattice thermal conductivity of 122 half-Heusler compounds using the temperature dependent effective potential method, we generate a data set sufficient in span to explore this issue. We show that random forest regression can fail to identify low lattice thermal conductivity compounds with random selection of training data. However, if the choice of training data is instead guided using feature and principal component analysis, it can drastically improve the ability to identify low lattice thermal conductivity compounds as well as model performance.

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Characterization of rattling in relation to thermal conductivity: Ordered half-Heusler semiconductors

Cited by 58 publications

References 63 publications

Establishing the carrier scattering phase diagram for ZrNiSn-based half-Heusler thermoelectric materials

Establishing the carrier scattering phase diagram for ZrNiSn-based half-Heusler thermoelectric materials

Biaxial Tensile Strain-Induced Enhancement of Thermoelectric Efficiency of α-Phase Se2Te and SeTe2 Monolayers

Lattice thermal conductivity of half-Heuslers with density functional theory and machine learning: Enhancing predictivity by active sampling with principal component analysis

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